فصلنامه پژوهش های جغرافیای طبیعی
پیاپی 93 (پاییز 1394)

Hydrograph of springs represents clearly all physical processes that control ground water flows inside aquifer (Kuto et al.، 2012، 41). Study of the curve can reveal information about structure and function of aquifer، particularly hydrodynamic parameters including permeability and storage (Troch et al.، 1993، 228). Analysis of recession curve has the advantage to calculate parameters of drainage mechanism such as recession coefficients. The volume of the primary discharge is sum of rapid and base flows and the specification of sub-regimes (Malık and Vojtkova، 2012). Identification of base flow properties and its prediction in dryperiod is necessary to determine the storage and to prevent it from pollution (Dewandel، et al، 2003). Karstic aquifers are an enormous reservoir of water in many regions of the world and with decline in quality and the amount of alluvial aquifers they got important more as a strategic hoard of water (suta، 2008، 856). The karstic aquifers are the main source of water for human society and ecosystem of Alvand basin. They also provide the base flow of Alvand and are important in initiation and continuation of civilization in this basin. The purpose of the study is to assess the development of karst in the aquifers of Alvand using the analysis of recession curve hydrograph. The methodology of this research is based upon literature evidence، field work data and analysis of the recession curve hydrograph. Thus، we have used qualitative and quantitative data from hydrographic and precipitation stations of Power Ministry from 1999 to 2010. Coefficient of variations of the springs’ discharge (CV)، the quality of water in the aquifers، and the hydrochemical parameters has been analyzed. Given the unequal development of karst in different parts of the aquifer، five springs (aquifers) have been selected to assess development of karst. These aquifers are including Rijab، Marab، Gelin، Sarab Garm and Gelodareh. To specify the type of flow system in karstic aquifers، hydrograph of recession curve have been analyzed. In order to calculate sub-regimes of laminar and turbulent flow، equations 1 and 2، respectively have also used. Equation 1 is an exponential function that was suggested for lamianr flows by Froccoyatsh and Palouk (1967). Equation 2 is linear function that was outlined by Kolmann for turbulent flows. Equation 1: Q_t=Q_0 e^ (-αt) Equation 2: Qt=Q0 (1-βt) The Rijab Spring has two laminar and turbulent sub-regimes. The equation of recession curve for this spring is as following: Qt = 2. 1e-0. 008t + 1. 25e-0. 001t + 510 (1-0. 29t). The degree of karstification of the Rijab aquifer is 5. 5. There are also karstic channels in this aquifer. The rapid flow in Rijab aquifer is charged mainly by sinkholes and large cavities. The flow is also discharges by channels inside the aquifer. Sarabgarm Spring based on equation of recession curve of Qt = 2. 01e-0. 001t + 1. 25e-0. 003thas two sub-regimes and the karstification is 2. 7. Golin Spring has two sub-regimes and recession curve as Qt = 0. 62e-0. 009t + 0. 46e-0. 001t. Karstification is also about 3. 7 with little channels. The equation is Qt = 0. 263e-0. 009t + 0. 175e-0. 001tfor Gelodareh with two laminar sub-regimes and 3. 7 karstification degree. There is just one flow regime (laminar) and many small channels. The equation is as Qt = 0. 725e-0. 002t + 0. 620e-0. 008t + 285 (1-0. 37t) for Marab spring. The equation indicates two laminar sub-regimes and a turbulent flow system with 5. 5 karstification degree. In Marab aquifer turbulent flow is prevailing. The aquifer is charged by sinkholes and is discharged by channels inside aquifer. Local differences in factors of karstification including lithology، tectonic، climate، elevation، slope and also physiographic characteristics of the drainage areas charging the aquifers in Alvand Basin cause variations in karstification and hydrodynamic behavior of aquifers. Analysis of rates of karstification، the values of Alpha، and also the number and the types of sub-regimes indicate heterogeneous karstic aquifers in Alvand Basin. Aquifers of Marab and Rijab are the most developed in karstification and Sarab Garm is the least in this terms. Geomorphology of surface terrain plays a major role in hydrodynamic behavior of aquifers. Physiography of the drainage basin where is charging aquifers plays also a role in hydrodynamic characteristics and the quantity and kinds of sub-regimes. In high elevation precipitation is more and evaporation is low. This cause more input into the aquifer that affect، in turn، the aquifer sub-regimes. Finally، this can be stated that three factors have the most importance in hydrodynamic properties and karstification of aquifers in Alvand Basin. These are geomorphology of surface karst، physiography of recharging basins، and elevation of the area.

Selecting the clear and transparent index for the precipitation using long-term homogeneous data is an important point for the researchers. Several investigations have led to different indexes for heavy rainfall. In some cases the specific amount of precipitation was used for heavy rainfall (Rahimzadeh 2005، Masoodian 2008 and and kamiguchi et al 2006) e. g. Alijani (2002) has suggested the precipitation more than 30 milimeter. Some investigators have used the percentage of daily precipitation as a heavy rainfall index (Mohammadi and Masoodian 2010) e. g. Easterling et al (2003) used the greatest annual 5-day total precipitation amount and the percent of annual precipitation، due to all 24-h rainfall totals exceeding the 95th percentile of daily amounts. A series of international workshops have introduced a set of indecators to show the effect of climate change on extreme events (Folland et al. 1999، Nicholla and Murray 1999، Manton et al. 2001). some investigators used several indecators as an index for heavy rainfall (Seibert et al 2005، Haylock et al 2006، Haylock and nicholis 2000، Osborn and Hulme2002، Simonov et al 2007، Vaidya and Kulkarni 2007، Campins et al 2006،Paddock and et al 2008، Kysely and Picek، 2007، Bukantis et al 2010، Schmidli et al 2002) e. g. Hänsel and Matcshullat (2009) to study monthly trends of daily heavy precipitation indicators used 22 heavy precipitation indicators (HPI) that may be classified in to the four groups “A”، “I”، “F” and “M”. “A” stands for average precipitation indicators like monthly precipitation totals and number of wet days. “I” comprises indicators measuring the precipitation intensity، like the SDPI (Simple Daily Precipitation Index) or the percentage of precipitation above the 95th percentile. The frequency of heavy precipitation events is studied by indicators in class “F”، while category “M” includes indicators of heavy precipitation events magnitude. zhang et al (2001) proved that annual and seasonal time series of heavy event frequency are obtained by counting the number of exceedances per year. Characteristics of the intensity of heavy precipitation events are investigated examining the 90th percentiles of daily precipitation، the annual maximum daily value، and the 20-yr return values. Based on the results، uses of percentile indecators are more common compared with threshold indicators and in some studies both indicators have been used. It seems that the use of heavy rainfall at some degree is depends on the geographical characteristics of the rainfall region. The natural ecosystems adapt themselves with the annual precipitation and extreme events in every region through the time. So the amount of precipitation that shows the heavy rainfall in a dry station، in a humid station can be recognized as normal. This study tries to find a simple method for indicating the heavy rainfall with regard to monthly trends based on daily data. Data and In regarding to determine an index for heavy precipitation، data of daily precipitation for 40 stations with synchronized meteorological data which are distributed homogeneously throughout the country in periods (1961-2011) were used. The probability (1، 5، 10، 20 and 50%) for the entire period of rainy days was calculated using the Weibul equation. A very high percentage of daily precipitation values were obtained with the test 1 percentage، so the occurrence of five percent of daily precipitation was used as an index. The relationship between the ratio of the total mean annual precipitation (mm) and No. of days with precipitation equal to or greater than one millimeter with a numerical coefficient which may provide the best indicator for the heavy rainfall. Factor analysis of these two components can be selected from among the eleven factors of rainfall data includes a total of 86 percent. Finally، the isohyet map was plotted using the numerical index by GIS so the heavy rainfall could be calculated for each part of Iran. To determine the appropriate numerical factor in Iran، all the stations are classified in to seven groups using K means cluster analyses، because of the different geographical characteristics and rainfall patterns. The average total annual rainfall was used to classify the groups. Then the numerical coefficient was calculated for each group separately. According to the proposed heavy rainfall index، the isohyet map was plotted. Using the isoline map of numerical coefficient calculated for each station or related area in order to estimate heavy rainfall. The average error between the proposed index and the five percent probability of daily precipitation is 0. 07. Only in Ardebil، Urumia، Dezful and chabahar port the error is more than one milimeter. There is no error in Ahvaz and Isfahan i. e. the proposed index is equal to the five percent probability of daily precipitation. The comparison between the heavy rainfall isohyet map and the total average annual precipitation and the No. of days with precipitation equal to or greater than one milimeter in Iran shows the same distribution.

This research concerns the automatic extraction of alluvial fans using four methods of segmentation from satellite data. Image segmentation divides images into partitions، which is typically used to recognize objects or other relevant purposes in digital images (Fu، 2013:3260). Alluvial fan always becomes a landform that attracts human as a location for living because of Fresh water and appropriate soil for drinking، cultivating، making pottery، making mud-brick and other activities (Maghsoudi & azizi، 2012:23). Therefore، alluvial fan extraction is significant in the planning of engineering geomorphology and other related disciplines. During recent years، many segmentation techniques have been developed (Ranasinghe، 2008). In this research، the most popular segmentations are presented and then those that are appropriate to identify alluvial fans of geomorphology were introduced. In general، Land-surface segmentation has demonstrated a great potential to improve geomorphological mapping، it enables better representations of geomorphological objects. Segmentation divides land-surface into relatively homogeneous areas، by polygons based on input criteria. Segmentation results are used to identify objects and their classification (Drăguţ et al، 2013). The main objective of this research is to introduce and implement algorithms for geomorphological landforms segmentations that the target landforms are alluvial fans and bahada in this research. The selected study area is in Yazd basin and in order to test in the generalizability of selected methods، the similar alluvial Fans of the central city of Yazd province have been selected. Briefly، importance of segmentations in geomorphology is in the extraction of landform objects، landform classification، landform isolation and identification details of landforms. Materials and Methods are based on processing segmentation on the high-resolution images of Geoeye-1 as well as the ASTR-1 multispectral Satellite images within the E-Cognition Developer© software from Trimble company. Arc Catalog and arc GIS are used for production of mentioned layers in the proposed flowchart. In this study، two main approaches have been used in the construction segmentation. In the Top-down Segmentation، objects of image are divided into smaller parts of itself. Top-down approaches are approximately implemented by three algorithms: 1. Chessboard segmentation 2. Quadtree-based segmentation 3. Contrast Split Segmentation. The forth methods for segmentation is called multi-resolution segmentation that is the most popular method in the bottom-up segmentation approach (Baatz and Schäp، 2000). We have described the four methods، and then each of those methods have been executed on the satellite images within the mentioned platforms، The outputs of each segmentation processing have been evaluated based on visual interpretation of images. According to the flowchart proposed، outputs of segmentation have been separately overlapped on the high-resolution Geo-eye images that are used the ArcGIS environment. Also the existing map of geomorphology was used for improving visual interpretation. In the study not only were used the top-down segmentation but also Bottom-up Segmentation approaches were used. The segmentation results of the four methods in the E-Cognition Developer© software from Trimble company was as follows: In short، the first method converts the image into a square shape that its output is a chessboard image. In the second method، the entire image is divided into four squares of the same size using the standard deviation or other criteria as a separate factor، then Each square is also divided into four smaller parts until to a defined threshold and so on these divisions continue Until the objects are separated from each other based on shape and color homogeneity. This method will produce narrow strip initial segments for features with a large length-width ratio (e. g. Roads، waterways، strip erosion types…) that is suitable for extraction of narrow objects in the context images. In the third method، the objects are separated by polygons from each other based on threshold values that indicate the degree of difference between darkness and brightness. We were able to extract details of the alluvial fans (e. g. Shadow of gully erosion، oued،) using contrast segmentation method. The forth methods، the image pixels or small objects are combined based on the criterion of homogeneity in successive with neighboring pixels or objects to lead to the production of larger objects. Therefore objects with homogeneous color and shape are combined to form a larger one. This technique is based on region growing concepts، in other words one or some known pixels are developed by the rest of unknown pixels based on a criterion. On the basis of the results، it was concluded that two algorithms are popular and applicable in geomorphology: A) The multi-resolution algorithm is precise and high performance to identify the geometry of the alluvial fans of Yazd basin; B) Contrast split segmentation has been successful to identify details on the body of the alluvial fans like to gully erosion، shadows، roads، Oued. Finally، in order to examine in the testability of selected methods، the multi-resolution algorithm has executed the similar Fans in other parts of the central city of Yazd province that its results has proved the generalizability of these methods، Because the algorithm is repeated four times to identify and extraction of the boundaries of alluvial fans، that outputs showed quite similar in the morphology of alluvial fan.

The main perspective in seasonal prediction of precipitation، is presenting a qualitative prediction for upcoming seasons. Information gained from such predictions can be used for decision making in various deciplines such as agriculture، water management and hydropower production. Besides، it can help for reducing the adverse effects of climatic changes like drought and flood. But General Ciculation Models (GCMs) outputs have coarse resolution (>100 km). Dynamical downscaling is a method for obtaining high-resolution climate data from relatively coarse resolution global climate models which do not capture the effects of local and regional forcing in areas of complex surface physiography. GCMs outputs at spatial resolution of 150-300 km are unable to resolve important sub-grid scale features such as clouds and topography. Many impacts models require information at scales of 50 km or less. As suchm، several statistical and dynamical methods are developed to estimate the smaller-scale information. Dynamical downscaling uses a limited area، high resolution model (a regional climate model: RCM) driven by boundary conditions from a GCM to derive smaller scale information. The aim of this study was application of RegCM4 dynamic model (Reginal climate model) in forecasting rainfall and improving the outputs using post processing techniques in northwest Iran during period 1982-2011. The recorded data of precipitation were collected from Urmia، Tabriz، Ardebil and Khuy Stations. The data required for running the regional climate model RegCM4 were adopted from center ICTP (International Centre for Theoretical Physics)، in the format of NetCDF including three sets of weather data، NNRP1 with a 6-hour-scale and a horizontal resolution of 2. 5°×2. 5° on the reanalysis databases of National Center of environmental prediction of United States، sea surface temperature، (SST) with a horizontal resolution of in 1°×1° from the type of SST belonged to America and National Oceanic and Atmospheric surface SURFACE، which were consisted of three topographic data GTOPO، the vegetation or land use، GLCC، and the soil type data GLZB، with a horizontal resolution of 30×30 seconds from United States Geological Survey، for the period 1982 to 2011. In order to implement the dynamic model، a test was conducted to determine the Convective Precipitation scheme and the amount of horizontal resolution for the year 2009 (as a normal year)، Accordingly، Kuo scheme with minimum mean bias error (MBE)، in comparison with observed precipitation in 36 synoptic stations of the region، was implemented as the main scheme، horizontal resolution of 30 × 30 square kilometers، the number of grid points including 152 in longitude (iy) and 168 in latitude (ix) was conducted during the statistical period of 1982 to 2011. Geographical area center implemented in the intended period was located in 30. 5 degrees north latitude and 50 degrees east longitude respectively. The output of the model included atmospheric data (ATM)، surface cover (SRF) and radiation cover with the format of NetCDF، each containing a large number of meteorological variables among which except precipitation from the Model (tpr)، 9 variables that were associated more with precipitation including q2m و t2m، ps، v1000، v500، u1000، u500،omega1000، omega500 were extracted. For post-processing the output of the model، the Multi-Layer Perceptron (MLP) and in Moving Average (MA) methods were used. For MLP Entering variables were 10 aforementioned variables and the target variable was observatory precipitation in the stationary point. At any one time، 80% of the data at the beginning of the series were for train and final 20 percent of data was used for test. The results of the study demonstrated that، in the study area، the mean bias error of raw annual precipitation outputs of the RegCM4 model was 124. 3 mm in the validation period، which by conducting Post Processing، reduced to 8. 9 mm. In the seasonal and monthly time scales، also، mean bias error of the were 31. 1 and 10. 4 mm، respectively، which were reduced to -0. 3 and zero mm، respectively، after post processing. The MA model was the prefered post processing method، in all time scales. In conclusion، it can be stated that the RegCM4 regional climate model with the said implementing conditions and in the study area، contained، mainly، overestimate in precipitation forecasting. However، the application of post-processing will optimally reduce bias. The appropriate method is also the simple moving average (MA) method.

Thunderstorms pose a significant threat to modern societies and their assets. Despite their local-scale characteristics، severe thunderstorms and associated extreme events like heavy rainfall، hail، gusts، or tornadoes، cause considerable damage to agriculture، buildings، or infrastructure facilities. Thunderstorms are highly localized and largely stationary weather systems affecting a limited area of about 20–50 km2، depending on the size of the cumulus tower. They are associated with shower clouds in which electrical discharges can be seen as lightning and heard as thunder on the ground، and they represent an advanced stage in the development of convection in moist air. The importance of rainfall generated by thunderstorms lies in the fact that it is largely torrential and of high intensity، and as a result much is lost as runoff which causes flooding. Basically thunderstorms occur more frequently above land areas in the warm season، while they are more frequent in the cold season over oceans. A lot of factors impact on their occurrence. Among them the most important are the thermodynamic and kinematic states of the atmosphere، topography، land cover، and its coastal configuration and atmospheric circulation issues. Ardabil is located in the northwest of the country، for this reason it has always been under the influence of the thunderstorms. Due to the geographic location and specific local conditions in this region، every year numerous thunderstorms happen in this area and cause severe damages in the agriculture، utilities and in restructure sectors. From this point of view، studying this phenomenon in detail and identifying the synoptic patterns of the ground surface and upper levels in which lead to the occurrence of thunderstorms in Ardebil are vital and important for the region. For this study، firstly the related data of Ardabil thunderstorms had been received from the Meteorological Agency of Ardabil. Within the related codes with the thunderstorms، codes from 90 to 99 during the period of 20 years (from 1992 to 2012) were used. After the initial Ardabil thunderstorm’s data analyzing، the 88 observational days that thunderstorm occurred in it were identified، and out of the 88 days، 43 days، that were compatible with the observational hours of4 for the NOAA data (3:30، 9:30، 15، 30، 21، 30) were used، for the patterning، so that the done research not to have any time contradiction with the upper atmosphere data and to be justified with the interpretation and analysis. Then، for the patterning and extraction of patterns in the upper atmosphere and ground surface، the related data to the pressure of the ground surface and geo potential height were obtained from the site which belongs to the National Center for Environmental Prediction (NCEP). So as to do this research the environmental to circulation method was used. In this case، first based on the recorded data in the Ardabil station، the occurred thunderstorms were identified and then by using the clustering، extraction and identification of the patterns for the ground surface and upper atmosphere launched، that leading to the occurrence of this phenomenon. For the classification and extraction of the ground surface pressure patterns and geo-potential height with the level of 500 hpa، the diverse kinds of hierarchical clustering methods tested، and finally based on the results، the clustering method into the Euclidean distance was known as the best method and the results of that were reflected in the following research. Result and Discuss: According to the results of hierarchical clustering، 4 patterns on the ground surface and in the level of 500 hpa were identified that the extracted patterns could justify beautifully the Ardabil thunderstorm occurrence. The ground surface patterns that lead to the occurrence of thunderstorms include pattern 1: the formation of low pressure on India، Siberia and high pressure on northern Europe and west of China، pattern 2: the formation of low pressure on the Ganges Valley، Persian Gulf and North Europe and high pressure on Siberia and west of China، pattern 3: the formation of low pressure on India and Persian Gulf and high pressure on Siberia and west of China، pattern 4: the formation of high-pressure on the central Asia and front occurring in the northwest of Iran. Also the patterns of geo-potential height with the level of500 hpa that lead to the occurrence of thunderstorms include pattern 1: the formation of the trough on the east Mediterranean and the placement of Ardabil in east of trough، pattern 2: the formation of the omega blocking on the northern parts of the Caspian sea and placement of Ardabil in southwest of that، pattern 3: the occurring of the cut-off blocking with low pressure on the central and east of the Turkey and placement of the Ardabil in east of the trough made by that، and pattern 4: the occurring split flow blocking in central Europe and placement of the Ardabil in east of trough. Different patterns according to the results of hierarchical clustering in the ground surface and in upper atmosphere are impressive on Ardabil thunderstorm precipitation. In the ground surface، the formation of low pressure on the Ganges valley، southwest of Persian Gulf، Siberia and northern Europe، also high pressure on the northern Europe، Siberia، west of China and the Central Asia played a significant role in the thunder precipitation occurrence. On the other hand in upper atmosphere، the study area in the east of trough and the formation of different patterns of blocking (omega، Split flow and cut-off low pressure) provided the condition so the thunder precipitation in Ardabil to be occurred.

Precipitation plays an important role in the global energy and water cycle. Knowing just the amount of precipitation reaching the ground water for assessment and management of land use، agriculture and hydrology، such as flood and drought risk reduction is so important. Assessment of climate change and its effects require long-term rainfall analysis in all spatial scales. Growing concern in the scientific community over whether there is a significant change in the amount of precipitation? (Nicholls and Alexander، 2007). 29% reduction in the daily maximum water flow caused by higher temperatures and increased evaporation with any change in rainfall causing drought in southern Canada during the years 1847 to 1996 (Zhang، Harvey، Hogg and Yuzyk، 2001). Recently summer drought caused by unusually dry heating in areas related to tropical West Pacific and Indian Ocean (Andreadis، Clark، Wood، Hamletand and Lettenmaier،2005; Pagano and Garen، 2005) including studies of climate change on global precipitation regimes. Germer (2008) has examined monthly variations in rainfall، floods، droughts and runoff in the Yangtze River Basin in China. In another study، Dao (2004) studied the daily variation of rainfall in semi-arid regions of northern China. Raziyy and Azizi (2008) said that topography and latitude are main factors of controlling the precipitation in the west of Iran. Also، Asakereh (1386) has investigated spatiotemporal variation in Iran precipitation. The results show that about 51. 4% of rainfall areas in the Iran have changed. The researcher suggested that factors share of rainfall Iran in precipitation changes be investigated. In this context، the author aims to explore the development of spatiotemporal changes of the rainfall pattern with access to the available and reliable database and the new approach to extract patterns and possible trends in the data. This paper investigated the spatial patterns of precipitation amount trends in cold period of year، for Iran between 1950 and 2009. We used of reanalysis monthly data of GPCC with 0. 5*0. 5 spatial resolution in Iran (From 44E until 63. 5E and 25N until 40N) and global & local Moran’s spatial autocorrelation methods. Global Precipitation Climatology Center data accuracy is measured by the geographical weighted regression (GWR) method. Spatial autocorrelation of precipitation data were extracted by global Moran Index. Global Moran index shows only the overall clustering of precipitation data. Therefore، to detect the different local patterns spatial autocorrelation، local Moran was used. The index measured spatial differences in rainfall amounts between each grid point and its neighboring points and evaluated its significant level. Trend analysis of spatial patterns configured based on Man Kendall’s τ nonparametric test. Geographically weighted regression between the global climatology center data and station data showed that gridded data has verified acceptable to replace the station data. Rainfall Gridded data and station data an average correlation of 76% has had. Global spatial autocorrelation results that precipitation data in all of the month shown significant positive spatial autocorrelation (or clustered pattern). Local spatial autocorrelation results that each month shown proprietary precipitation pattern and monthly precipitation entailed any significant trends. October shows the lowest average index values and dispersion in rainfall patterns has taken. Unlike the months of December rainfall patterns have shown concerted. A spatial clustering map shows، usually in October، a strong spatial cluster is formed on the southern coast of the Caspian Sea. However، during the months of November and December، a strong spatial cluster formed in Zagros on rain again. In February and March the Caspian cluster is reduced in proportion severity. Conclusion Temporal variations of the No، high - high points and No، low-low points in all months showed no significant change. This suggests a lack of space to expand or reduce the size of the cluster rainfall during the study period Comparison between pervasive drought events and Low value of Global Moran’s Index shown a strong relationship between them. Thereupon should be used of other variables for water defect researching. Comparing of general Moran index values and widespread drought in Iran showed that the low index values based on the years of drought. Results suggest that should evidence of dehydration in other climatic variables such as temperature and evaporation search.

Land use change and its effect on soils is one of the important factors in decreasing soil quality. Nowadays because of rapid growth of the population، vast areas of the forest lands are changed into agricultural lands but chemical properties of the soils are commonly affected by changing in land usage. Converting the forest lands into agricultural lands is one of the prevalent issues in Iran، especially in north of Iran، nevertheless، relevant studies considering the effects of land use change is very limited and lack of enough and suitable studies due to quantifying of these effects is so significant. Because of that، this study was carried out in order to investigate the impact of changing in usage of forest lands in to the dry farming lands (canola) and paddy lands on some chemical properties of soil such as: pH، organic carbon، total nitrogen، available phosphorous and potassium، electrical conductivity and cation exchanging capacity in Zarin Abad area of Sari، in north of Iran. In order to study the effect of changing in usage of forest lands (Hyrcanian forest) into the dry farm lands (canola) and paddy lands on some chemical properties of soil in Zarin Abad area of Sari، Iran، this research was conducted as factorial design in complete randomize block. samples of soil from each land use were collected in four replications from 2 depths of 0-20 and 20-50 centimeter. Samples were dried and passed from the 2mm sieve، then amount of the organic carbon was determined by the method of wet oxidation. Total nitrogen of the soil was measured by Kejeldal method. To calculate the soil available phosphorous، samples were extracted in two ways: Olson (for measuring available phosphorous in soil samples with pH=7) and Bray-Kortz (for measuring available phosphorous in soil samples with pH=7). then the amount of phosphorous in each extraction was determined with Expectrophotometer device. Available potassium was measured by extraction with Ammonium acetate with pH=7 and Flame photometer device. Cation Exchanging Capacity was also determined by Bawer method. To measure the reaction and the electrical conductivity of the soil’samples، after making saturation mud، the amount of reaction (pH) was measured by pH meter in each sample. The amount of electrical conductivity after extracting from saturation mud was determined in extractions from each sample by Ec meter. Then the analysis of data was done after doing normalization test with Colomogrof-Smirnof test in SPSS program. Comparison of the averages of data was done with Duncan test. Results showed that land use change from forest lands (Hyrcanian forest) into paddy lands، increased soil reaction from 6. 43 to 7. 52 but change to dry farming lands (canola) had no significant effect on soil reaction. Land use change from forest lands into dry farm lands caused decrease in the amount of organic carbon about 46. 5 percent which was about 38 percent in paddy lands. Amount of total nitrogen was decreased in land use change from forest usage into dry farm usage but this decrease was not significant in forest lands change into paddy lands. While land use change caused increase about 4 times in amount of available phosphorus in dry farming lands and increased about 2 times in lands that converted to paddy lands but it had no effect on amount of available potassium and cation exchanging capacity. The lowest amount of electrical conductivity was observed in dry farming lands. Correlation coefficients between parameters showed positive and significant correlations between organic carbon with available potassium and electrical conductivity. There were positive correlations between electrical conductivity with amount of available potassium and soil reaction. Amount of available phosphorus showed a positive relationship with cation exchanging capacity too. Land use change caused changes in some soil chemical properties and each property affected the amount of others so considering the ecological importance of Iran’s northern forests، results of this study showed the necessity of more accuracy and attention to adjust the unfavorable effects of land use change by applying efficient methods of land management in these areas.

E Precipitation is a vital component in the hydrological cycle. Its spatio-temporal variations has great environmental an socioeconomic impacts. The spatial variation of rainfall is depending upon many factors. Some of this variation is due to synaptic systems and some others is formed by local physiographical characteristic of station such as elevation from sea level، slope، windward and leeward slopes، land cover and land use and etc…. if the rainfall is formed by widespread and pervasive synoptic system it can be exist a significant spatial similarity and homogeneity in amount of given rainfall in all over the region which is affected by synoptic system. But if the rainfall is dominated by the local factors the higher heterogeneity of given amount rainfall can be expected. In this study، we used the 20-years monthly average precipitation (1990-2010) for 42 synoptic stations، in the west and north western portion of iran which include 6 province namly: the East and West Azerbaijan، Kurdistan، Ilam، Kermanshah، Hamadan and Zanjan. We preparation this data as an long term average of monthly precipitation for each station and then import them to GIS by metric Orojected coordinate system (PCS). We used Moran،s Index as an Spatial statistic approach to investigate the spatial relations of monthly precipitation. This tool measures spatial autocorrelation (feature similarity) based on both feature locations and feature values simultaneously. Given a set of features and an associated attribute، it evaluates whether the pattern expressed is clustered، dispersed، or random. The tool calculates the Moran''s I Index value and both a Z score and p-value evaluating the significance of that index. In general، a Moran''s Index value near +1. 0 indicates clustering while an index value near -1. 0 indicates dispersion. However، without looking at statistical significance you have no basis for knowing if the observed pattern is just one of many، many possible versions of random. In the case of the Spatial Autocorrelation tool، the null hypothesis states that «there is no spatial clustering of the values associated with the geographic features in the study area». When the p-value is small and the absolute value of the Z score is large enough that it falls outside of the desired confidence level، the null hypothsis can be rejected. If the index value is greater than 0، the set of features exhibits a clustered pattern. If the value is less than 0، the set of features exhibits a dispersed pattern. The morans I Statisic for spatial autocorrelation is given as 1) Moran index 2) Where Zi is the diviation of an attribute for feature I frome its mean، wij is the spatial weight between feature i and j، n is total number of object and S0 is aggregate of al spatial weight. We found the amount of monthly given rainfall in the study region in cool season (November to February) reveal a significant positive autocorrelation. and on the other hand the spatial variation coefficient of rainfall in these month is smaller than other remaining month. the revealed Moran’s I indicated in the 4 mentioned months so strong significance that somebody cannot Assigning this spatial homogeneity to chance and randomness. In the cool season the study area which located in west and northwestern of Iran is dominated by westerly and following them the atmospheric synoptic systems entrance to country and affecting all of the country area then the rainfall is formed by widespread and pervasive synoptic system has significantly spatial similarity and homogeneity in all over the region and the strong positive autocorrelation is revealed in these months. In the warm season (July، September، August، October، and May) we find inverse condition. The Moran’s index in these months was very small and near to zero. We couldn’t detect any significant spatial autocorrelation in these months. In our study region the warm season especially summer season (July to September) is the dry period of year. The occurred rainfall in these months is usually sporadic and non-comprehensive. These rainfalls usually characterized by being showery which is formed by local atmospheric convective a cells. In this type of rainfall the different local physiographical characteristics such as elevation from sea level، slope، windward and leeward slopes، land cover and land use and etc… have a substantial roll in formation and spatial distribution of this rainfall. So that the difference physiographical characteristic of each region this local formed precipitation is not too similar. In the warm season absenting westerly in this region، the local physiographical characteristics determinant the occurred rainfall and due to this physiographical dissimilarity in the region، heterogeneity of given amount rainfall can be rise. The spatial variation coefficient of rainfall in warm season is very higher than col season. The revealed Moran’s I was not significant in 0. 95 confident level and there are no spatial pattern in this warm. Our finding indicated that only the cool season months including November، December، January and February reveal a significant spatial autocorrelation in 0. 95 and 0. 91 confident level.

Identification of active tectonic zones، especially in regions of structural converge to the potential risk of considerable importance to them. On the other hand، due to the physical limitations of surveys in these areas with rough topography is difficult and conflicting. In this study، using remote sensing techniques، Geomorphometry and limited fieldwork، morphometric and geomorphologic characteristics Roudak in the North East of Tehran TecDEM model was implemented in Matlab software، the digital data (digital elevation model) and extraction have been analyzed. The results and analysis of structural elements Morphotectonic Publications such as the longitudinal profile of the river، flow directions، basin morphology، the change in slope، equal maps، calculate indicators of tectonic geomorphology and curves of hypsometry and sleekness of the strain and the resulting action tectonic forces have responded reflect changes on the watershed and the young and active Morphotectonic it now. To investigate active tectonics in the study area، using geological maps scale 1:100،000 for، knows، MarzanAbad and Tehran area that it is located in the catchment area، to evaluate the number and types of faults in the area Also in the region، and evidence of active tectonic faulting in the area including the separation of large and small pieces of stone from steep slopes that raise the risk of loss in the study and were observed. Finally using DEM and DTM software Tecdem1. 0 ArcGis10. 0 and overall catchment area Roudak and then sub-basins have been extracted. To study the tectonic activity in the area of software Tecdem، DEM، you must map to bring Depression less، so that a height map of the study area should be free of any surface discontinuities. The map is based on the tectonic influence of topography changes and the resulting change in classification confirms drainage basin. The different algorithms in terms of accessions to run on different software by researchers to analyze the tectonic activities there; one of them recently for the analysis of geomorphic used by Annex TecDEM is. The rider in the first step، attention and effort to develop a single system to run most of the techniques used in the analysis of tectonic TecDEM based software MATLAB، in order to understand the tectonic activity of the Digital Elevation Model DEM uses. The capabilities of this software can be used to create a longitudinal profile of the river، the calculation of flow directions، extracting watershed، determine the slope change، tectonic maps of the equal and index noted. According to the index calculated by the single tail and troughs of the index gradient، the gradient of the river slope، topographic symmetry of the integral cross hypsometry، the active tectonics of the basin has been proven. The sub watershed 4 Garmabdar highest rates of basin and watershed activities Meygoon lowest rates of tectonic activity index based on the concavity and slope index and slope gradient. While the rate of tectonic activity، based on the topography of the transverse symmetry، basins 1 and 3 shows the maximum tilt. There are also all sub-basin hypsometry curves of young people in the catchment basins (4) shows that most of its convexity. Despite the difference in the indices، the mean indicate tectonic regime in the study area and in the area of youth. Tectonic activity، the amorphous network of rivers. Study of the nature of this disorder can be associated with a great understanding of the origin and direction of tectonic activity areas. Because the pattern of drainage network development، including indicators that are very sensitive to changes in tectonic activity (chlorine Bunter، 1996:1). Studies conducted in recent years the role of neotectonic activity in the formation of river systems (destroyed، 15:2003). Dents and powerful gradient analysis of indicators for neotectonic study by analyzing the flow of the river that the tectonically active regions go، is. Match field studies and library studies were carried out on the geological map of 1:100،000 in the studies performed by the software Tecdem and indicators tectonic geomorphology and maps produced by the Demonstrates the proper use and application of these methods in the analysis of tectonic zones is Tecdem especially in relation to areas that may not be possible to study its field.

Water is the most important parameter in the development of human societies. One of the pillars in the development of water resources is the investigation of environmental conditions and environmental compatibility of the project.. Identify areas vulnerable to pollution can play a major role in development strategies. In most area of Iran، which is located in the arid and semi-arid region، groundwater is the most important water supply for agricultural، domestic and industrial uses. In most areas، the risk of groundwater contamination is considered to be a serious restriction for this source. Therefore avoid groundwater contamination in groundwater resources management is essential. One of the methods to identify vulnerable areas is the use of qualitative indicators. Among the qualitative indicators، the DRASTIC index of vulnerability to groundwater pollution has many applications. This index is obtained by combining seven different parameters. Each of the parameters of the model، investigate the potential and the possibility of accepting the contamination of the aquifer and each parameter has a unique weight. So far، most studies which have been done with this indicator have led to aquifer vulnerability mapping and calibration and the model calibration and optimization of input coefficients is less studied. This study was conducted to investigate the vulnerability of Birjand aquifer and increase the accuracy of the model. In this study for estimate the vulnerability to contamination، different hydro-geological data were used. These data are including depth to water table، net recharge، aquifer environment، soil environment، topography، environment unsaturated and hydraulic conductivity. Then، plain vulnerability maps were computed using DRASTIC index with combination of these data. One of the most important and influential parameter in environmental contaminations is nitrate. In this project، in order to evaluate the vulnerability of the Birjand aquifer obtained by DRASTIC model، observed data of nitrate in Birjand aquifer which was tasted in 1390 were used. According to the concentration of the Nitrate in the observation wells; model was calibrated using Analytical Hierarchy Process (AHP). For this purpose، parameters of the DRASTIC model، with respect to the inconsistency rate as stated، was modeled by AHP method using of software provided by the Export choice modeling، and calibration weight and then analysis these weights was done using the incompatibility coefficient. DRASTIC layers was obtained Using interpolation and classification tools in the Arc Gis 10. 2 software. According to the preliminary results، depth to the water table and slope parameters has the highest weight in aquifer data. Also، recharge rate of the aquifer in two parts of urban areas، due to the recycled water، has higher weight than in other parts of the aquifer. Also، according to drilling logs، influence testing، pedological testing and the aquifer environment classified in two classes، the soil environment in four classes and unsaturated zone in tree classes. Considering to the high levels of recharge due to return flow were divided in urban areas and agricultural land and according to the test results of pedological and influence، hydraulic conductivity parameters in three classes. After obtaining the required parameters for vulnerability assessment، vulnerability map of the Birjand. Aquifer was obtained using DRASTIC model. Incompatibility factor was chosen as one of the major constraints to optimize the coefficients and weights DRASTIC model. Based on the obtained results and the value of using AHP method incompatibility factor of less than 0. 08 is selected as the best option for analysis. Figure classification of Birjand aquifer vulnerability was presented based on DRASTIC with weight of AHP modelare including four categories very low، low، moderate and moderate to high. The results show the sensitivity of the aquifer in the outlets due to the high water table. The results provided by the DRASTIC model showed that the model was not accurate enough to identify vulnerable areas and it is need to calibrate the weights of models. Therefore، in this study using Analytical Hierarchy Process (AHP) and observational data of nitrate، model was calibrated in the Birjand aquifer. The results showed that the modified DRASTIC model has the higher accuracy in compare with common DRASTIC model، and there is a good correlation between improved weights using AHP method and the observed nitrate concentration in observation wells.